def test_diffImageSmooth(self):
image = np.arange(12.).reshape(4, 3)
diff_image = diffImageSmooth(image, dy='x')
np.testing.assert_array_almost_equal(diff_image, np.array(
[[0.346482, 0.390491, 0.346482], [0.346482, 0.390491, 0.346482], [0.346482, 0.390491, 0.346482],
[0.346482, 0.390491, 0.346482]]))
with self.assertRaises(Exception):
diffImageSmooth(np.arange(4), dy='x')
def cleanSensingImage(im, dy=0, sigma=None, order=3, fixreversal=True, removeoutliers=False, verbose=0):
""" Clean up image from sensing dot
Args:
im (numpy array)
dy (int or str): direction for differentiation
order (int)
fixreversal (bool)
removeoutliers (bool)
Returns:
ww (image): processed image
"""
verbose = int(verbose)
removeoutliers = bool(removeoutliers)
im = np.array(im)
if sigma is None:
imx = diffImage(im, dy=dy, size='same')
else:
imx = diffImageSmooth(im, dy=dy, sigma=sigma)
if order >= 0:
vv = fitBackground(imx, smooth=True, verbose=verbose, fig=None,
order=int(order), removeoutliers=removeoutliers)
ww = (imx - vv).copy()
else:
ww = imx.copy()
if fixreversal:
ww = fixReversal(ww, verbose=verbose)
return ww